Marius Oberle

Reduction of Human Induced Uncertainty Through Appropriate Feedback Design

Due to the reduction of development periods and a concurrent increase of product complexity, knowledge about the usage and resulting strain of products becomes more and more important. Thereby the human impact on the uncertainty of usage is essential, yet hardly known or quantified. A first approach for the reduction of uncertainty could be the enhancement of information by means of additional feedback. Therefore, a laboratory study is conducted to investigate the amount of uncertainty as well as the impact of feedback on uncertainty, using a simple placement task. The study shows that by enhancing the amount of information given to the user, the systems strain and with this the uncertainty can be reduced significantly. Further an appropriate concept for the representation of information has to be developed, as the mere enhancement of information could also lead to an enhancement of uncertainty.

Experimentelle Untersuchung des menschlichen Einflusses auf die Unsicherheit in der Mensch-Technik-Interaktion

ZusammenfassungIm Beitrag werden Untersuchungsergebnisse aus vier Laborstudien zur Quantifizierung des menschlichen Einflusses auf die Unsicherheit in der Mensch-Technik-Interaktion vorgestellt. Im Fokus steht die Untersuchung des menschlichen Einflusses auf die Belastung von technischen Systemen hinsichtlich Handlungsausführung und Handlungssequenz sowie die Untersuchung des Einflusses von digitalem Feedback auf die resultierende Belastung. Das gewonnene Wissen kann zur Anpassung des Designs sowie zur Implementierung einer geeigneten Informationsdarbietung für den Nutzer verwendet werden und trägt somit zur Reduzierung von Unsicherheit bei. Praktische Relevanz. Auf Basis der durchgeführten Studien und deren Ergebnisse kann für die untersuchten Kontexte die resultierende Unsicherheit beschrieben, quantifiziert und zukünftig prädiziert werden. Zudem ist die Zurückführung der resultierenden Unsicherheit auf spezifische menschliche Einflussgrößen möglich. Darauf aufbauend bieten die Ergebnisse die Grundlage zur Entwicklung einer Resilienz förderlichen und unsicherheitsgerechten Gestaltung von Mensch-Maschine-Schnittstellen.AbstractThe paper presents results from four laboratory studies on the quantification of the human influence on the uncertainty of human-machine interaction. Focused is the investigation of the human impact onto the stress of technical systems regarding the execution and sequence of human action, as well as the investigation of the influence of digital feedback on the resulting system stress. The knowledge gained can be used to adapt the design and appropriate implementation of information representation for the user, thus contributing to the reduction of uncertainty. Practical Relevance. Based on the conducted studies, the resulting uncertainty for the investigated contexts can be described, quantified and predicted. In addition, the resulting uncertainty can be ascribed to specific human influencing factors. Based on this, the results provide the foundation for the development of resilient and uncertainty-suitable human-machine interfaces.

Increasing Software Security by Using Mental Models

Cybercrime is a global problem and the economic damages are enormous (Center for Strategic and International Studies. http://csis.org/ [1]). Identifying reasons for software vulnerabilities is an important issue with some researchers assuming software developers to be part of the problem. As most developers aren’t security experts they create insecure and thus vulnerable software. To avoid this, a tool that supports software developers in dealing with security issues should be developed. This work uses the structure formation technique (Scheele et al. in Dialog-Konsens-Methoden zur Rekonstruktion Subjektiver Theorien: die Heidelberger Struktur-Lege-Technik (SLT) (1988) [2]) as a first step to develop the mental models of software developers when dealing with security measures. A core definition of mental models is compiled and the results of a pilot study deliver valuable information for the supporting tool. In further research the developed mental models of novices’ (software developers) should be compared with the mental models of security experts. On this basis the reliability of the novices’ mental models can be reviewed and occurring problems identified.

Representation of Human Behaviour for the Visualization in Assembly Design

This article extends the Uncertainty Mode and Effects Analysis (UMEA) to human effects and uses ontologies to connect human driven uncertainty data to the corresponding parts in an aircraft CAD-Assembly. Still, human behaviour is one of the major sources of uncertainty in the product usage phase. Hence, using uncertainty data of human behaviour for product design becomes increasingly important, especially for the control of uncertainty in load carrying systems. In this context, the exchange of semantically enriched uncertainty data between different domains and domain specific applications guarantees the consistency of the data prevents misinterpretation and enables the reuse of existing data for future design decisions.